RRepoGEO

REPOGEO REPORT · LITE

udecode/dotai

Default branch main · commit 9ad1c690 · scanned 7/1/2026, 7:37:42 PM

GitHub: 1,151 stars · 82 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface udecode/dotai, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition README H1 and opening paragraph to clarify purpose

    Why:

    CURRENT
    Shared skills for coding agents. Skills are the main routing layer. This repo is the canonical source for reusable udecode workflows; downstream repos should link to these skills instead of copying long SKILL.md files around.
    COPY-PASTE FIX
    Shared skills and reusable workflows for AI coding agents. This repository is a canonical collection of agent-native routines and automations, designed to be linked and reused across udecode projects. It provides specific, composable agent capabilities, not a general SDK or CLI assistant.
  • hightopics#2
    Add comprehensive topics for better categorization

    Why:

    CURRENT
    ai, claude-code, codex, cursor
    COPY-PASTE FIX
    ai, ai-agents, agent-workflows, llm-ops, code-review-automation, devops-automation, github-actions, automation, workflows, agent-skills
  • highlicense#3
    Add a LICENSE file and declare it in the README

    Why:

    COPY-PASTE FIX
    Add a LICENSE file (e.g., MIT License) to the repository root. Then, add a line to the README, for example: "This project is licensed under the MIT License – see the [LICENSE](LICENSE) file for details."

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface udecode/dotai
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
jupyter/notebook
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. jupyter/notebook · recommended 1×
  2. jupyterlab/jupyterlab · recommended 1×
  3. microsoft/vscode · recommended 1×
  4. GitHub Copilot · recommended 1×
  5. Tabnine · recommended 1×
  • CATEGORY QUERY
    How to build reusable programming skills and workflows for AI coding assistants?
    you: not recommended
    AI recommended (in order):
    1. Jupyter Notebooks (jupyter/notebook)
    2. JupyterLab (jupyterlab/jupyterlab)
    3. VS Code (microsoft/vscode)
    4. GitHub Copilot
    5. Tabnine
    6. Codeium
    7. Git (git/git)
    8. GitHub
    9. GitLab (gitlabhq/gitlabhq)
    10. Bitbucket
    11. Cookiecutter (cookiecutter/cookiecutter)
    12. Poetry (python-poetry/poetry)
    13. PDM (pdm-project/pdm)
    14. pip (pypa/pip)
    15. pytest (pytest-dev/pytest)
    16. JUnit (junit-team/junit5)
    17. NUnit (NUnit/NUnit)
    18. MkDocs (mkdocs/mkdocs)
    19. Sphinx (sphinx-doc/sphinx)

    AI recommended 19 alternatives but never named udecode/dotai. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an AI agent toolkit for automating code review and pull request feedback management.
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot Enterprise
    2. CodeRabbit
    3. DeepSource
    4. Codiga
    5. GitLab Duo Code Suggestions
    6. CodiumAI
    7. SonarQube (SonarSource/sonarqube)

    AI recommended 7 alternatives but never named udecode/dotai. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of udecode/dotai?
    pass
    AI named udecode/dotai explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts udecode/dotai in production, what risks or prerequisites should they evaluate first?
    pass
    AI named udecode/dotai explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo udecode/dotai solve, and who is the primary audience?
    pass
    AI named udecode/dotai explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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udecode/dotai — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite